1155 Senior Data Architect (Azure / Databricks / Cosmos DB)

• Design and own enterprise-scale data platform architectures on Azure.

• Assess existing data environments and identify opportunities to improve scalability, performance, maintainability, and data quality.

• Define and implement modern data platform architectures using Azure services and Databricks.

• Design reusable and metadata-driven data ingestion frameworks.

• Architect and optimize structured and unstructured data processing solutions.

• Design and maintain scalable data models and analytical platforms.

• Define both tactical improvements and long-term target-state architectures.

• Create architecture documentation, technical specifications, and implementation guidelines.

• Collaborate with engineering teams, stakeholders, and business users to translate requirements into scalable solutions.

• Establish best practices for data governance, architecture standards, data quality, and platform reliability.

• Support engineering teams during implementation and architecture adoption.

• Proven experience as a

with end-to-end architecture ownership.

• Strong hands-on experience with the

.

• Minimum 4 years of recent Azure experience.

• Strong expertise with: Azure Synapse Analytics, Azure Data Factory (ADF),Azure Data Lake Storage (ADLS),Azure SQL / SQL Server, Azure Cosmos DB, Databricks

• Strong experience with: Data Engineering, Data Warehousing, ETL/ELT architectures, Data Modeling, Incremental Processing, Cloud Data Platforms

• Advanced SQL and Python skills.

• Experience designing and implementing large-scale cloud data solutions.

• Strong experience working with both structured and unstructured data.

• Excellent communication and stakeholder management skills.

The successful candidate should demonstrate deep knowledge of:

• Synapse Pipelines

• Spark Pools

• Serverless SQL

• Dedicated SQL Pools

• Workload optimization and architecture design

• Data lake integration patterns

• Large-scale analytical platforms

• Data modeling, Partition key strategy, Indexing, Scalability design, Throughput and RU optimization, Cost optimization, Consistency models, Change Feed, Distributed database architectures

• Strong architecture ownership and decision-making experience.

• Experience modernizing and improving existing data platforms.

• Ability to quickly assess complex environments and provide actionable recommendations.

• Experience designing reusable and scalable ingestion frameworks.

• Deep understanding of structured and unstructured data processing.

• Strong data modeling experience for enterprise analytics platforms.

• Ability to balance short-term business needs with long-term architectural vision.

• Technology-neutral mindset when selecting tools and services based on requirements, scalability, performance, and cost.

• Experience producing implementation-ready architecture deliverables.

• Lakehouse architecture experience.

• Experience with AI-driven analytics solutions.

• Data governance and compliance experience.

• Experience supporting enterprise reporting and analytics environments.

• Knowledge of modern cloud-native architecture patterns.

• Azure Synapse Analytics, Azure Data Factory, Azure Data Lake Storage, Azure SQL / SQL Server, Azure Cosmos DB, Databricks, Python, SQL, ETL/ELT, Data Warehousing, Data Modeling

• Challenging enterprise-scale projects.

• Opportunity to drive architecture decisions and platform modernization initiatives.

• Collaboration with international teams.

• Long-term cooperation and professional growth opportunities.

• Innovative and supportive work environment.

Originally posted on Himalayas